Module Database

Information for module BIOL7015

This module is available for 2017/18

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Module code:BIOL7015 (Add to my personalised list)
Title:Computational Biology
Credit value:.5
Division:Division of Biosciences
Module organiser (provisional):Dr Max Reuter
Organiser's location:Biological Sciences
Available for students in Year(s):2, 3
Module prerequisites:BIOL1002, STAT6101 or equivalent 
Module outline:Topics to be covered: 1. Statistics (12 lectures + 6 x 1 hour practicals) - linear models - generalised linear models - multivariate statistics - maximum likelihood and Bayesian approaches - resampling and permutation - experimental design and power analysis 2. Modelling (4 lectures +2 x 1 hour practicals) - dynamical models: population dynamics and epidemiology - population and quantitative genetics - game theory - optimisation - simulation approaches 3. Bioinformatics (4 lectures +2 x 1 hour practicals) - biological databases - methods in DNA, RNA and protein analysis  
Module aims:The aim of this course is to give 2nd year students a more advanced understanding of the quantitative approaches used in contemporary biological sciences.  
Module objectives:Students should be able to design meaningful experiments and perform appropriate statistical analyses on a wide variety of biological data. In terms of mathematical modelling, students will acquire a basic knowledge of modelling and simulation approaches used in different circumstances. They will be able to read and understand theoretical papers, as well as have the necessary foundation to start building simple models themselves. In bioinformatics, finally, students will learn about the kinds of data that are publicly available and the ways to access them. They will also learn about current computational approaches used to analyse different classes of data. 
Key skills provided by module:This course will provide you with computational and analytical skills that will be useful across many disciplines of biology and other branches of science. You will also learn how to interpret and present data and models and improve your general computer literacy. 
Module timetable: 
Module assessment:Essay one (2,500 words) 25.00%
Three departmental tests (90 minutes each) 50.00%
Essay two (2,500 words) 25.00% 
Taking this module as an option?: 
Link to virtual learning environment (registered students only) 
Last updated:2015-08-17 20:57:57 by ucbtksr